燕山大学学报2024，Vol.48Issue(6)：528-536,9.DOI:10.3969/j.issn.1007-791X.2024.06.007
基于YOLOv9-B模型的港口船舶红外检测方法
lnfrared ship detection in harbor based on YOLOv9-B model
摘要
Abstract
To further enhance the safety and intelligence of port operations,intelligent detection methods for ships in the harbor under complex conditions are studied in this paper.It primarily addresses issues of detection inaccuracies caused by imaging blur due to environmental factors and the small size of vessel targets resulting from shooting angles.A high-precision infrared vessel detection model based on YOLOv9-B is proposed.Firstly,a multi-scale spatial attention module is designed,wherein traditional convolutions in spatial attention are replaced with multiple dilated convolutions to expand the receptive field and capture more local information.Secondly,a branch fusion attention mechanism is devised to enhance the focus on small and blurry targets by introducing efficient channel attention and multi-scale spatial attention,thereby reducing the loss of target information during feature fusion.Finally,the RepNCSPELAN4 module in YOLOv9 is replaced with the C2f module to strengthen feature extraction capabilities and improve detection accuracy.The ablation experiments are conducted on the infrared ship dataset and the self-constructed dataset in this paper,and the results show that compared with the YOLOv9 model,the proposed model improves the mAP by 1.6%and 1.9%,and improves the detection speed by 3.2 and 1.2 fps,respectively.At the same time,the comparative experiments show that the proposed model is superior to other mainstream models.关键词
YOLOv9-B/红外船舶检测/多尺度空间注意力机制/分支融合注意力机制Key words
YOLOv9-B/infrared ship detection/multi-scale spatial attention mechanism/branch fusion attention mechanism分类
计算机与自动化引用本文复制引用
曹子玉,张文宇,闫磊,王云坤,李鑫滨..基于YOLOv9-B模型的港口船舶红外检测方法[J].燕山大学学报,2024,48(6):528-536,9.基金项目
国家自然科学基金资助项目(62271437,62373318) （62271437,62373318）
河北省博士后科研择优资助项目(B2023003005) （B2023003005）
河北省创新能力提升计划资助项目(22567619H) （22567619H）
省级重点实验室绩效补助经费项目(22567612H) （22567612H）
